title: Predicting the ultraviolet radiation protection by polyester-cotton blended woven fabrics using nonlinear regression and artificial neural network models.
abstract: BACKGROUND
  Ultraviolet protection factor (UPF) of fabric is mainly influenced by fabric cover which is dependent on the primary fabric construction parameters like yarn count and thread density. UPF can be modeled by using these primary fabric parameters as inputs by the help of nonlinear regression as well as artificial neural network (ANN).
  
  
  OBJECTIVE
  The objective of this study is to develop prediction models for fabric UPF using nonlinear regression and ANN techniques and compare their relative efficacy.
  
  
  METHODS
  Thirty-six woven fabric samples were produced by varying weft related parameters like proportion of polyester, weft count and pick density. Nonlinear regression and ANN models were developed from same experimental data sets. Prediction accuracy of both the models was evaluated and compared. Trend analysis was performed to check the generalization ability of the ANN model.
  
  
  RESULTS
  UPF was well estimated from the three primary fabric parameters by both the nonlinear regression and ANN models. However, ANN model demonstrated better prediction accuracy than the nonlinear regression model.
  
  
  CONCLUSIONS
  Fabric UPF can be predicted with high degree of accuracy using ANN and nonlinear regression models. These models can be used to estimate the UPF of woven fabrics without spectrophotometer based test.
authors.affiliation: Department of Textile Technology, Indian Institute of Technology Delhi, New Delhi, India. piyali.iit10@gmail.com
authors.forename: Piyali
authors.initials: P
authors.lastname: Hatua
authors.forename: Abhijit
authors.initials: A
authors.lastname: Majumdar
authors.forename: Apurba
authors.initials: A
authors.lastname: Das
mesh_terms: D032561:Cotton Fiber; D016571:Neural Networks, Computer; D011091:Polyesters; D014466:Ultraviolet Rays / Q000009:adverse effects*
chemical_list: D011091:Polyesters
keywords: artificial neural network; nonlinear regression; polyester-cotton blend; trend analysis; ultraviolet protection factor